v1v2 (latest)

Differentially Empirical Risk Minimization under the Fairness Lens

4 June 2021

Cuong Tran

My H. Dinh

Ferdinando Fioretto

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Papers citing "Differentially Empirical Risk Minimization under the Fairness Lens"

36 / 36 papers shown

Title
Mitigating Disparate Impact of Differentially Private Learning through Bounded Adaptive Clipping Linzh Zhao Aki Rehn Mikko A. Heikkilä Razane Tajeddine Antti Honkela 135 0 0 02 Jun 2025
Private Rate-Constrained Optimization with Applications to Fair Learning Mohammad Yaghini Tudor Cebere Michael Menart A. Bellet Nicolas Papernot 140 0 0 28 May 2025
Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Survey Jing Liu Yao Du Kun Yang Yan Wang Yan Wang ... Zehua Wang Yang Liu Peng Sun Azzedine Boukerche Victor C.M. Leung 165 4 0 03 May 2025
Trustworthy Machine Learning via Memorization and the Granular Long-Tail: A Survey on Interactions, Tradeoffs, and Beyond Qiongxiu Li Xiaoyu Luo Yiyi Chen Johannes Bjerva 301 3 0 10 Mar 2025
Learning with Differentially Private (Sliced) Wasserstein Gradients David Rodríguez-Vítores Clément Lalanne Jean-Michel Loubes FedML 165 0 0 03 Feb 2025
SoK: What Makes Private Learning Unfair? Kai Yao Marc Juarez 114 0 0 24 Jan 2025
PFGuard: A Generative Framework with Privacy and Fairness Safeguards Soyeon Kim Yuji Roh Geon Heo Steven Euijong Whang 167 0 0 03 Oct 2024
Differentially Private Data Release on Graphs: Inefficiencies and Unfairness Ferdinando Fioretto Diptangshu Sen Juba Ziani 91 1 0 08 Aug 2024
Differentially Private Clustered Federated Learning Saber Malekmohammadi Afaf Taik G. Farnadi FedML 125 3 0 29 May 2024
Privacy at a Price: Exploring its Dual Impact on AI Fairness Mengmeng Yang Ming Ding Youyang Qu Wei Ni David B. Smith Thierry Rakotoarivelo 70 1 0 15 Apr 2024
Differentially Private Fair Binary Classifications Hrad Ghoukasian S. Asoodeh FaML 128 3 0 23 Feb 2024
Generalization Error of Graph Neural Networks in the Mean-field Regime Gholamali Aminian Yixuan He Gesine Reinert Lukasz Szpruch Samuel N. Cohen 127 4 0 10 Feb 2024
Disparate Impact on Group Accuracy of Linearization for Private Inference Saswat Das Marco Romanelli Ferdinando Fioretto FedML 100 4 0 06 Feb 2024
On the Impact of Output Perturbation on Fairness in Binary Linear Classification Vitalii Emelianov Michael Perrot FaML 114 0 0 05 Feb 2024
A Simple and Practical Method for Reducing the Disparate Impact of Differential Privacy Lucas Rosenblatt Julia Stoyanovich Christopher Musco 77 3 0 18 Dec 2023
SoK: Unintended Interactions among Machine Learning Defenses and Risks Vasisht Duddu S. Szyller Nadarajah Asokan AAML 203 4 0 07 Dec 2023
On The Fairness Impacts of Hardware Selection in Machine Learning Sree Harsha Nelaturu Nishaanth Kanna Ravichandran Cuong Tran Sara Hooker Ferdinando Fioretto 119 3 0 06 Dec 2023
Bias-Aware Minimisation: Understanding and Mitigating Estimator Bias in Private SGD Moritz Knolle R. Dorfman Alexander Ziller Daniel Rueckert Georgios Kaissis 66 2 0 23 Aug 2023
Survey of Trustworthy AI: A Meta Decision of AI Caesar Wu Yuan-Fang Li Pascal Bouvry 142 3 0 01 Jun 2023
FairDP: Certified Fairness with Differential Privacy K. Tran Ferdinando Fioretto Issa M. Khalil My T. Thai Nhathai Phan 138 0 0 25 May 2023
On the Fairness Impacts of Private Ensembles Models Cuong Tran Ferdinando Fioretto 130 6 0 19 May 2023
Participatory Personalization in Classification Hailey J James Chirag Nagpal Katherine A. Heller Berk Ustun 111 5 0 08 Feb 2023
An Empirical Analysis of Fairness Notions under Differential Privacy Anderson Santana de Oliveira Caelin Kaplan Khawla Mallat Tanmay Chakraborty FedML 116 8 0 06 Feb 2023
Fairness Increases Adversarial Vulnerability Cuong Tran Keyu Zhu Ferdinando Fioretto Pascal Van Hentenryck 97 7 0 21 Nov 2022
Differential Privacy has Bounded Impact on Fairness in Classification Paul Mangold Michaël Perrot A. Bellet Marc Tommasi 133 21 0 28 Oct 2022
Stochastic Differentially Private and Fair Learning Andrew Lowy Devansh Gupta Meisam Razaviyayn FaML FedML 110 15 0 17 Oct 2022
A Closer Look at the Calibration of Differentially Private Learners Hanlin Zhang Xuechen Li Prithviraj Sen Salim Roukos Tatsunori Hashimoto 123 3 0 15 Oct 2022
Fairness in Forecasting of Observations of Linear Dynamical Systems Quan Zhou Jakub Mareˇcek Robert Shorten AI4TS 191 5 0 12 Sep 2022
How Much User Context Do We Need? Privacy by Design in Mental Health NLP Application Ramit Sawhney A. Neerkaje Ivan Habernal Lucie Flek 116 4 0 05 Sep 2022
Disparate Impact in Differential Privacy from Gradient Misalignment Maria S. Esipova Atiyeh Ashari Ghomi Yaqiao Luo Jesse C. Cresswell 163 34 0 15 Jun 2022
How unfair is private learning ? Amartya Sanyal Yaxian Hu Fanny Yang FaML FedML 136 24 0 08 Jun 2022
Pruning has a disparate impact on model accuracy Cuong Tran Ferdinando Fioretto Jung-Eun Kim Rakshit Naidu 145 41 0 26 May 2022
Pre-trained Perceptual Features Improve Differentially Private Image Generation Fredrik Harder Milad Jalali Asadabadi Danica J. Sutherland Mijung Park 192 31 0 25 May 2022
SF-PATE: Scalable, Fair, and Private Aggregation of Teacher Ensembles Cuong Tran Keyu Zhu Ferdinando Fioretto Pascal Van Hentenryck 95 12 0 11 Apr 2022
Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey Ferdinando Fioretto Cuong Tran Pascal Van Hentenryck Keyu Zhu FaML 105 67 0 16 Feb 2022
A Stochastic Optimization Framework for Fair Risk Minimization Andrew Lowy Sina Baharlouei Rakesh Pavan Meisam Razaviyayn Ahmad Beirami FaML 175 23 0 24 Feb 2021